Cost-Effectiveness of FreeStyle Libre for Glucose Self-Management Among People with Diabetes Mellitus: A Canadian Private Payer Perspective
Bibliographic record
Abstract
For people living with diabetes, effective glucose monitoring is a key component in diabetes care, helping to reduce disease burden, complications, and healthcare utilization. Sensor-based glucose monitoring systems, which can provide more comprehensive information about glucose levels than capillary-based self-monitoring of blood glucose (SMBG), are becoming established among people living with diabetes. The objective of this study was to assess the cost-effectiveness of glucose monitoring with FreeStyle Libre systems, compared with SMBG, from the perspective of a Canadian private payer. The analysis used the validated, person-level microsimulation model DEDUCE (Determination of Diabetes Utilities, Costs, and Effects). Analyses were conducted separately for populations of people with type 1 and type 2 diabetes mellitus (T1DM; T2DM), with time horizons of 40 and 25 years, respectively. T2DM treatment was assumed to be 84% non-insulin, 10% basal insulin, and 6% multiple daily injections of insulin. The effect of FreeStyle Libre was modeled as reductions versus SMBG in glycated hemoglobin level (T1DM, − 0.42%; insulin-treated T2DM, − 0.59%; non-insulin-treated T2DM, − 0.3%) and in acute diabetic events (hypoglycemia and diabetic ketoacidosis). Costs (in 2023 Canadian dollars (Can$)) and utilities were discounted at 1.5%. Outcomes were assessed as costs and quality-adjusted life years (QALYs). In both populations, FreeStyle Libre was dominant to SMBG, providing more QALYs at a lower cost (T1DM: + 1.25 QALYs, − Can$32,287 costs; T2DM: + 0.48 QALYs, − Can$8091 costs). Reductions were seen in the cumulative incidence of all complications (except blindness in the T1DM analysis). FreeStyle Libre was dominant to SMBG in all scenarios tested. Probabilistic sensitivity analysis showed that FreeStyle Libre had a 100% probability of being dominant to SMBG for T1DM and a 91% probability of being dominant for T2DM. This economic analysis shows that, from a Canadian private payer perspective, FreeStyle Libre is cost-effective compared with SMBG for all people living with diabetes. Glucose monitoring is important for people living with diabetes. Effective glucose monitoring can reduce the risk of hypoglycemia (low blood sugar), diabetic ketoacidosis (a potentially life-threatening complication which occurs when the body has low insulin and high blood sugar levels), and long-term complications. This can be done using finger sticks and test strips or sensor-based devices such as the FreeStyle Libre systems. In this study, we modeled the effect of FreeStyle Libre use in persons living with type 1 or type 2 diabetes mellitus in Canada using the DEDUCE economic model. In both analyses, FreeStyle Libre use was predicted to lead to better outcomes (measured as quality-adjusted life years—a measure of health which combines life expectancy with quality of life) for people living with diabetes while reducing costs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".